Cheng-Hung Liu — accepted AI-conference papers

2024

Exploring Space Efficiency in a Tree-based Linear Model for Extreme Multi-label Classification

He-Zhe Lin, Cheng-Hung Liu, Chih-Jen Lin

EMNLP 2024main

Extreme multi-label classification (XMC) aims to identify relevant subsets from numerous labels. Among the various approaches for XMC, tree-based linear models are effective due to their superior efficiency and simplicity. However, the space complexity of tree-based methods is not well-studied. Many…

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2022

On the Use of Unrealistic Predictions in Hundreds of Papers Evaluating Graph Representations

Li-Chung Lin, Cheng-Hung Liu, Chih-Ming Chen, Kai-Chin Hsu, I-Feng Wu, Ming-Feng Tsai +1

AAAI 2022technical

Prediction using the ground truth sounds like an oxymoron in machine learning. However, such an unrealistic setting was used in hundreds, if not thousands of papers in the area of finding graph representations. To evaluate the multi-label problem of node classification by using the obtained represen…

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